Research

Liquid crystals provide a versatile platform for studying order, elasticity, and self-organization in soft matter. My research establishes multiscale models that bridge molecular chemistry to mesoscale structures and macroscopic response. By combining continuum theories with coarse-grained simulations, I quantify how chirality, curvature, and confinement drive defect formation and patterning. These models have revealed pathways for controlling morphology in chiral, confined, and hybrid liquid-crystalline systems.

Representative works:

• Palacio-Betancur, V. et al. Curvature and confinement effects on chiral liquid crystal morphologies. Soft Matter (2023). doi:10.1039/d3sm00437f
• Palacio-Betancur, V. et al. Cuboidal liquid crystal phases under multiaxial geometrical frustration. Soft Matter (2020). doi:10.1039/c9sm02021g

Many soft materials operate far from equilibrium, where flow, fields, and confinement couple to generate emergent order. I investigate nonequilibrium assembly and hydrodynamic effects in liquid-crystalline suspensions and nanocomposites, focusing on how these forces can be harnessed to direct structure formation. My work has shown how hydrodynamic fields and boundary constraints mediate the dynamic organization of colloidal and molecular systems, providing design principles for active and adaptive materials.

Representative works:

• Villada-Gil, S.*, Palacio-Betancur, V.* et al. Directing the far-from-equilibrium assembly of nanoparticles in confined liquid crystals by hydrodynamic fields. Soft Matter (2021). doi:10.1039/d0ss02221g
• Gharbi, I., Palacio-Betancur, V. et al. Liquid crystal films as active substrates for nanoparticle control. ACS Applied Nano Materials (2021). doi:10.1021/acsanm.1c00680

To enable reproducible, quantitative comparison between computation and experiment, I develop open-source tools that bridge simulation, theory, and data representation.

The LCPOM package reconstructs polarized optical microscopy (POM) images from director fields obtained in simulations, enabling one-to-one visual and quantitative comparison with experiments.

In my postdoc, I introduced graph-theoretic molecular descriptors that encode the topology of molecular charge distributions. This approach links quantum-level electrostatics to macroscopic polarity and phase behavior, providing interpretable features for machine learning and predictive design of polar nematic materials.

Representative works:

• Chen, C., Palacio-Betancur, V. et al. LCPOM: Precise reconstruction of polarized optical microscopy images of liquid crystals. Chemistry of Materials (2024). doi:10.1021/acs.chemmater.3c02425
• Palacio-Betancur, V., Jackson, N. E. Molecular charge topologies govern polar nematic ordering. Submitted to JACS (2025).